舌面彩色三维点云的舌体分割及舌裂纹提取  

Tongue segmentation and tongue crack extraction of tongue 3D color point cloud

作　　者：王鹏[1] 杨文超[1] 孙长库[1] 郭世珍 

机构地区：[1]天津大学精密测试技术及仪器国家重点实验室,天津300072 [2]天津中医药大学中医工程学院,天津300193

出　　处：《红外与激光工程》2017年第B12期82-89,共8页Infrared and Laser Engineering

基　　金："十二五"国家科技支撑计划(2012BAI25B05)

摘　　要：随着舌诊现代化的进一步发展,合理地利用舌面彩色三维点云数据成为中医诊疗各类疾病并获取客观量化信息的关键环节。通过将现代三维点云处理技术与传统中医诊断经验进行有效融合,提出了基于扩展快速点特征颜色直方图(Fast Point Feature&Color Histogram,FPFCH)特征值的欧式聚类舌体分割算法及基于法线区域分割的舌裂纹提取算法。FPFCH特征值由扩展快速点特征直方图(Fast Point Feature Histogram,FPFH)分量和色调(Hue,H)分量组成,作为欧式聚类分割后舌体点云的判别条件。基于法线区域分割即通过对法线夹角阈值进行判别,提取舌裂纹点云。经过大量实验可知,上述算法能够有效地完成舌体分割和舌裂纹提取,为舌诊客观化研究提供了技术支持。With the further development of modern tongue diagnosis, reasonable use of tongue 3D color point cloud data has become a key step in TCM diagnosis and treatment of various diseases and obtaining the objective and quantitative information. By combining modem 3D point cloud processing technology with traditional TCM diagnosis experience, an algorithm for the Euclidean cluster segmentation of tongue based on the Fast Point Feature ＆ Color Histogram （FPFCH） eigenvalue and the region segmentation based on normal of tongue crack extraction was proposed. The FPFCH eigenvalues consisted of the extended Fast Point Feature Histogram （FPFH） component and the Hue （H） color component as the discriminant condition of the tongue point cloud after the Euclidean cluster segmentation. The area was segmented by judging the threshold of the normal line angle and the point cloud of the tongue crack was extracted. A large number of experiments show that the algorithm can effectively complete the tongue segmentation and tongue crack extraction, which provides technical support for the research of object diagnosis of the tongue.

关 键 词：三维点云处理 舌体分割 FPFCH特征值 舌裂纹提取 舌诊客观化 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置]